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liuchang-skill-creator六场技能创建器

Agent Skill

liuchang-skill-creator 用于辅助安全审计、权限检查和凭据风险排查,适合在 OpenClaw 中需要复核安全边界、认证流程或敏感配置时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

5,341

周安装

214

GitHub Stars

公开资料未说明

下载量

1,729
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:liuchang-skill-creator(六场技能创建器)
来源仓库:https://github.com/liuchang8877/liuchang-skill-creator
安装命令:
openclaw skills install liuchang-skill-creator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install liuchang-skill-creator

简介

六场技能创建器用于审核、编辑和改进 Agent Skill,提升技能安全性和功能性。

  • 支持权限检查、凭据风险排查及代码审计,适合开发流程中的质量把控环节。
  • 在需要创建或审查新技能时自动激活,依赖本地脚本执行验证步骤。
  • 安装后请检查脚本路径与宿主兼容性,避免误执行敏感操作。
  • liuchang-skill-creator 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

version
1.2.0
name
skill-creator
description
Create, edit, improve, or audit AgentSkills. Use when creating a new skill from scratch or when asked to improve, review, audit, tidy up, or clean up an existing skill or SKILL.md file. Also use when editing or restructuring a skill directory (moving files to references/ or scripts/, removing stale content, validating against the AgentSkills spec). Triggers on phrases like "create a skill", "author a skill", "tidy up a skill", "improve this skill", "review the skill", "clean up the skill", "audit the skill".

Skill Creator

This skill provides guidance for creating effective skills.

About Skills

Skills are modular, self-contained packages that extend agent capabilities by providing specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific domains or tasks.

What Skills Provide

  1. Specialized workflows - Multi-step procedures for specific domains
  2. Tool integrations - Instructions for working with specific file formats or APIs
  3. Domain expertise - Company-specific knowledge, schemas, business logic
  4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks

Core Principles

Concise is Key

The context window is a public good. Skills share the context window with everything else the agent needs.

Default assumption: The agent is already very smart. Only add context it doesn't already have.

Set Appropriate Degrees of Freedom

  • High freedom (text-based): Multiple approaches valid, decisions depend on context
  • Medium freedom (pseudocode/scripts): Preferred pattern exists, some variation acceptable
  • Low freedom (specific scripts): Operations are fragile, consistency critical

Anatomy of a Skill

skill-name/
├── SKILL.md (required)
│   ├── YAML frontmatter (name, description)
│   └── Markdown instructions
├── scripts/          - Executable code
├── references/       - Documentation to load as needed
└── assets/           - Files used in output

Skill Creation Process

Step 1: Understanding the Skill

Understand concrete examples of how the skill will be used. Ask:

  • "What functionality should this skill support?"
  • "Give me examples of how this skill would be used"
  • "What would a user say that should trigger this skill?"

Step 2: Planning Reusable Contents

Analyze each example to identify:

  • Scripts: Same code being rewritten repeatedly?
  • References: Documentation needed for context?
  • Assets: Templates or files used in output?

Step 3: Initialize the Skill

Run the init script:

scripts/init_skill.py <skill-name> --path <output-directory> [--resources scripts,references,assets]

Step 4: Edit the Skill

Write Frontmatter

---
name: skill-name
description: Clear description of what the skill does AND when to trigger it. Include specific contexts, use cases, and examples. This is the PRIMARY triggering mechanism - put all "when to use" info here, not in the body.
---

Description is for the model: When the agent starts a session, it scans all skill descriptions to decide "is there a skill for this request?" So the description must clearly state:

  • What the skill does
  • Specific triggers/contexts for when to use it
  • Concrete examples of user requests that should activate it

Write SKILL.md Body

Keep under 500 lines. Use references/ for detailed content.

Step 5: Package the Skill

scripts/package_skill.py <path/to/skill-folder>

🎯 Advanced Features

Gotchas Section (Highly Recommended)

The highest-signal content in any skill is a Gotchas section. Build this from common failure points the agent runs into.

## Gotchas

- **File encoding**: Always use UTF-8, otherwise parsing fails
- **Large files**: Split files over 10MB before processing
- **API rate limits**: Add 1-second delay between requests

Best practice: Update gotchas over time as you encounter new failure points.

Memory & Storing Data

Skills can include memory by storing data within them:

## Memory

This skill stores data in `~/.my-skill/data.json`. On each run, the agent reads this file to understand previous context.

Storage options:

  • Append-only log files (simple)
  • JSON files (structured)
  • SQLite database (complex queries)

Important: Store data in a stable location outside the skill directory. Use ${CLAUDE_PLUGIN_DATA} if available - data in the skill directory may be deleted on upgrades.

On Demand Hooks

Skills can include hooks that are only activated when called:

## Hooks

When activated, this skill registers:
- `/careful`: Blocks dangerous operations (rm -rf, DROP TABLE)
- `/freeze`: Only allows edits in specific directories

Use these for opinionated behaviors you don't want always on, but are extremely useful sometimes.

Setup Configuration

For skills requiring user-specific context, store configuration in a config file:

## Setup

This skill requires configuration in `config.json`:
- `api_key`: Your API key
- `channel`: Slack channel for notifications

If config is missing, ask the user for required fields.

Product Verification

For skills that need verification, include test patterns:

## Verification

After execution, verify the output:
1. Check file exists: `ls -la output/`
2. Run validation script: `scripts/validate.py output/file.json`
3. Take a screenshot for visual confirmation

Consider techniques:

  • Programmatic assertions on state
  • Video recording of output
  • Log file comparison with previous runs

📦 Distributing Skills

Option 1: Check into Repository

For small teams, check skills into the repo (e.g., ./skills/ or ./.claude/skills).

Option 2: Plugin Marketplace

For larger teams, create an internal marketplace where users can install skills. Document how to submit and review skills.

Measuring Skills

Track skill usage with a PreToolUse hook:

# Log when skill is triggered
@hook("PreToolUse")
def log_skill_usage(agent, tool_name, input):
    if tool_name == "Skill":
        log(f"Skill used: {input['skill_name']}")
    return input

This helps identify:

  • Popular skills vs underused ones
  • Skills that need improvement
  • Patterns in how skills are being used

📚 Progressive Disclosure Patterns

Pattern 1: Reference Files

# PDF Processing

## Quick Start
[basic example]

## Advanced Features
- **Form filling**: See [references/forms.md](forms.md)
- **API reference**: See [references/api.md](api.md)

Pattern 2: Domain Organization

bigquery-skill/
├── SKILL.md
└── references/
    ├── finance.md
    ├── sales.md
    └── product.md

Pattern 3: Conditional Details

## Editing Documents

For simple edits, modify XML directly.

**For tracked changes**: See [references/redlining.md](redlining.md)

Common Mistakes to Avoid

  1. Don't state the obvious: Agent already knows basics
  2. Don't put everything in SKILL.md: Use references/ for details
  3. Don't over-railroad: Give flexibility to adapt
  4. Don't skip gotchas: Build from real failures
  5. Don't forget setup: Ask for required config early

Quick Reference

PatternWhen to Use
scripts/Deterministic code, repeatedly rewritten
references/Documentation, schemas, examples
assets/Templates, images, output files
gotchasCommon failure points
hooksConditional behaviors
memoryPersistent context across runs
config.jsonUser-specific settings

Iteration Workflow

  1. Use the skill on real tasks
  2. Notice struggles or inefficiencies
  3. Identify what should be updated
  4. Implement changes and test again

Tip: Most skills begin as a few lines and a single gotcha. They get better because people keep adding to them as the agent hits new edge cases.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

90.12%
按下载量换算1,558

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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